DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
2. Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
3. The information disclosure statements (IDS) submitted on 05/18/2026 and 07/21/2026 have been received, entered into the record, and considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Response to Amendment
4. Receipt of Applicant’s amendment filed on 07/24/2026 is acknowledged. The amendment includes the amending of claims 1, 8, 10-11, and 13.
Claim Objections
5. The objections raised in the Office Action mailed on 04/24/2026 have been overcome by applicant’s amendment received on 07/24/2026.
Double Patenting
6. The rejections raised in the Office Action mailed on 04/24/2026 have been overcome by applicant’s amendment received on 07/24/2026.
Claim Rejections - 35 USC § 112
7. The rejections raised in the Office Action mailed on 04/24/2026 have been overcome by applicant’s amendment received on 07/24/2026.
8. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
9. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
10. Claim 14 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Specifically, it is unclear as to whether the claimed “first set of priority keywords” in the limitation “determining a first set of priority keywords for the candidate text” refers to the earlier claimed “first set of priority keywords” in the limitation “where the positive example is determined based on context-aware keywords generated based on a first set of priority keywords obtained from the candidate text and a second set of priority keywords obtained from the label” in parent independent claim 13.
Dependent claims 15-18 are rejected for incorporating the deficiencies of dependent claim 14.
Claim 14 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Specifically, it is unclear as to whether the claimed “second set of priority keywords” in the limitation “determining a second set of priority keywords for the label” refers to the earlier claimed “second set of priority keywords” in the limitation “where the positive example is determined based on context-aware keywords generated based on a first set of priority keywords obtained from the candidate text and a second set of priority keywords obtained from the label” in parent independent claim 13.
Dependent claims 15-18 are rejected for incorporating the deficiencies of dependent claim 14.
Claim 14 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Specifically, it is unclear as to whether the claimed “context-aware keywords” in the limitation “determining a set of context aware keywords from the first set of priority keywords and the second set of priority keywords” refers to the earlier claimed “context-aware keywords” in the limitation “where the positive example is determined based on context-aware keywords generated based on a first set of priority keywords obtained from the candidate text and a second set of priority keywords obtained from the label” in parent independent claim 13.
Dependent claims 15-18 are rejected for incorporating the deficiencies of dependent claim 14.
Claim Rejections - 35 USC § 101
11. The rejections (with respect to the carrier wave rejection for claims 8-12) raised in the Office Action mailed on 04/24/2026 have been overcome by applicant’s amendment received on 07/24/2026.
12. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
13. Claims (1-7), (8-12), and (13-20) are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under the 2019 PEG, when considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (step 1). If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea) (step 2A prong 1), and if so, it must additionally be determined whether the claim is integrated into a practical application (step 2A prong 2). If an abstract idea is present in the claim without integration into a practical application, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself (step 2B).
In the instant case, claims (1-7), (8-12), and (13-20) are directed to a method, a computer-readable media, and a system respectively. Thus, each of the claims falls within one of the four statutory categories. However, the claims also fall within the judicial exception of an abstract idea.
Under Step 2A Prong 1, the test is to identify whether the claims recite a judicial exception. The examiner notes that the claimed invention recites an abstract idea in that the instant application recites a mental processes, specifically labeling data.
The examiner further notes that claims (1-7), (8-12), and (13-20) recite a method, a computer-readable media, and a system for labeling data which is similar to themes defined above of method of mental processes such as performing the labeling data, and is similar to the abstract idea identified in the 2019 PEG in grouping “c” in that the claims recite certain methods of mental processes such as performing the labeling of data. The limitations, substantially comprising the body of the claim, recite a process of labeling data. The examiner notes that the claimed invention labels data. Because the limitations above closely follow the steps in labeling data, and the steps of the claims involve mental processes, the claim recites an abstract idea consistent with the “mental processes” grouping set forth in the 2019 PEG.
Claim 1:
A method comprising: receiving a candidate text;
receiving a label description;
obtaining a positive example and a negative example associated with the label description;
where the positive example is determined based on context-aware keywords generated based on a first set of priority keywords determined based on the candidate text and a second set of priority keywords determined based on the label description;
providing as an input to a generative model, the candidate text, the positive example, and the negative example;
determining a label probability estimate based on an output of the generative model; and
outputting an indication whether the candidate text corresponds to the label description based on the label probability estimate.
These limitations, as drafted, is an apparatus that, under its broadest reasonable interpretation, covers the performance of mental processes specifically labeling data. Labeling data has long before the modern computer was invented, and continues to be predominantly a product of human endeavor. The instant application recites labeling data. Moreover, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example can be performed by a human via their mind and/or pen & paper. Furthermore, the providing of an input of a candidate text, positive example, and negative example into a model can be performed by a human via their mind and/or pen & paper. Additionally, the claimed determining of a label probability estimate can be performed by a human via their mind and/or pen & paper. Moreover, the outputting of an indication on whether a candidate text corresponds to a label description based on a determined label probability estimate can be performed by a human via their mind and/or pen & paper. Because the limitations above closely follow the steps of labeling data, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind and/or pen & paper, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the 2019 PEG.
If the claims recite the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. The Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite “significantly more” at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites words “apply it” (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to an apparatus instructing the reader to implement the identified apparatus of mental processes of labeling data. The elements of the claim do not themselves amount to an improvement to the computer, to a technology or another technical field. Moreover, the receiving of candidate text is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Furthermore, the receiving of a label description is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Additionally, the output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application.
Here, the claim elements entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. In short, the claims have failed to integrate a practical application (see at least 84 Fed. Reg. (4) at 55). Under the 2019 PEG, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claim 1 does not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
With respect to the dependent claims, they have been considered and are not found to be reciting anything that amounts to being significantly more than the abstract idea. Claims 2-7 are directed to further embellishments of the central theme of the abstract idea in that the claims are directed to further embellishments of the labeling data of the steps of claim 1 and do not amount to significantly more.
Specifically, claim 2 is directed to the searching of documents via a generated defined query which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Additionally, claim 3 is directed to the defining of the positive example that is based on a text and a label which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Furthermore, claim 4 is directed to the determining of a label probability estimate which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Moreover, claim 5 recites the use of first and second weights on first and second label scores to determine a label probability which can be performed by the human mind and/or pen & paper and does not amount to significantly more.
Furthermore, claim 6 recites the defining of the first and second weights which can be performed by the human mind and/or pen & paper and does not amount to significantly more.
Additionally, claim 7 recites the vectorization of graph terms which can be performed by the human mind and/or pen & paper and does not amount to significantly more.
Claim 8:
A non-transitory computer-readable media comprising instructions that when executed by a computing device cause the computing device to perform a method comprising: receiving a candidate text;
receiving a label description;
obtaining a negative example and a positive example associated with the label description;
where the positive example is determined based on context-aware keywords generated based on a first set of priority keywords determined based on the candidate text and a second set of priority keywords determined based on the label description;
generating a prompt for a generative model based on the negative example and the positive example;
determining a label probability estimate by comparing a first ranked score of a positive example result generated by the generative model based on the prompt to a second ranked score of a negative example result generated by the generative model based on the prompt; and
determining that the candidate text corresponds to the label description based on the label probability estimate.
These limitations, as drafted, is an apparatus that, under its broadest reasonable interpretation, covers the performance of mental processes specifically labeling data. Labeling data has long before the modern computer was invented, and continues to be predominantly a product of human endeavor. The instant application recites labeling data. Moreover, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and negative example that are both associated with a label description can be performed by a human via their mind and/or pen & paper. Additionally, the claimed generation of a prompt can be performed by a human via their mind and/or pen & paper. Moreover, the claimed determining of a label probability estimate can be performed by a human via their mind and/or pen & paper. Furthermore, the determining of whether a candidate text corresponds to a label based on a label probability estimate can be performed by a human via their mind and/or pen & paper. Because the limitations above closely follow the steps of labeling data, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind and/or pen & paper, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the 2019 PEG.
The mere nominal recitation of generic computing components such as computer-readable media and a computing device do not take the claim out of certain methods of mental processes grouping. Therefore, the limitation recites an abstract idea.
If the claims recite the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. The Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite “significantly more” at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites words “apply it” (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to an apparatus instructing the reader to implement the identified apparatus of mental processes of labeling data. The elements of the claim do not themselves amount to an improvement to the computer, to a technology or another technical field. Moreover, the receiving of candidate text is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Furthermore, the receiving of a label description is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application.
Here, the claim elements entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. In short, the claims have failed to integrate a practical application (see at least 84 Fed. Reg. (4) at 55). Under the 2019 PEG, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claim 8 does not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
With respect to the dependent claims, they have been considered and are not found to be reciting anything that amounts to being significantly more than the abstract idea. Claims 9-12 are directed to further embellishments of the central theme of the abstract idea in that the claims are directed to further embellishments of the labeling data of the steps of claim 8 and do not amount to significantly more.
Specifically, claim 9 is directed to the defining of a first ranked score which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Additionally, claim 10 is directed to the generation of a defined positive example and defined negative example which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Furthermore, claim 11 is directed to the generation of a defined first score and defined second score which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more. Furthermore, the submission of a data to a search engine is a data transmission operation that is an insignificant data transmission operation that does not integrate the abstract idea into a practical application.
Moreover, claim 12 is directed to the defining of a corpus which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Claim 13:
A system comprising: one or more processors; and
one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to perform a method, the method comprising: obtaining a candidate text and a label associated with the candidate text;
generating an augmented training data including a positive example and a negative example;
where the positive example is determined based on context-aware keywords generated based on a first set of priority keywords obtained from the candidate text and a second set of priority keywords obtained from the label;
classifying the candidate text using a machine learning model trained with the augmented training data; and
outputting an indication that the candidate text corresponds to the label based on a result of classifying the candidate text using the machine learning model.
These limitations, as drafted, is an apparatus that, under its broadest reasonable interpretation, covers the performance of mental processes specifically labeling data. Labeling data has long before the modern computer was invented, and continues to be predominantly a product of human endeavor. The instant application recites labeling data. Moreover, the obtaining of a candidate text and label associated with the candidate text can be performed by a human via their mind and/or pen & paper. Additionally, the claimed generation of augmented training data that includes a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords obtained from candidate text and a second set of priority keywords obtained from a label and a negative example can be performed by a human via their mind and/or pen & paper. Moreover, the claimed classifying of candidate text can be performed by a human via their mind and/or pen & paper. Furthermore, the outputting of an indication on whether a candidate text corresponds to a label based on a classification can be performed by a human via their mind and/or pen & paper. Because the limitations above closely follow the steps of labeling data, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind and/or pen & paper, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the 2019 PEG.
The mere nominal recitation of generic computing components such as one or more processors and one or more computer storage media do not take the claim out of certain methods of mental processes grouping. Therefore, the limitation recites an abstract idea.
If the claims recite the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. The Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite “significantly more” at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites words “apply it” (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to an apparatus instructing the reader to implement the identified apparatus of mental processes of labeling data. The elements of the claim do not themselves amount to an improvement to the computer, to a technology or another technical field.
Here, the claim elements entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. In short, the claims have failed to integrate a practical application (see at least 84 Fed. Reg. (4) at 55). Under the 2019 PEG, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claim 13 does not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
With respect to the dependent claims, they have been considered and are not found to be reciting anything that amounts to being significantly more than the abstract idea. Claims 14-20 are directed to further embellishments of the central theme of the abstract idea in that the claims are directed to further embellishments of the labeling data of the steps of claim 13 and do not amount to significantly more.
Specifically, claim 14 is directed to the determination of different keywords which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more. Additionally, the submission of a query to a search engine is a data transmission operation that is an insignificant data transmission operation that does not integrate the abstract idea into a practical application. Additionally, the receiving of a response from the search engine is a data transmission operation that is an insignificant data transmission operation that does not integrate the abstract idea into a practical application.
Additionally, claim 15 is directed to the defining of a received response from a search engine which is a data transmission operation that is an insignificant data transmission operation that does not integrate the abstract idea into a practical application.
Moreover, claim 16 is directed to the storage of data which is a data storage operation that is an insignificant data storage operation that does not integrate the abstract idea into a practical application.
Furthermore, claim 17 is directed to the vectorization and subsequent comparison of different vectors which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Additionally, claim 18 is directed to the use of a cosine computation between vectors which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Moreover, claim 19 is directed to the defining of a negative example which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Furthermore, claim 20 is directed to the obtaining of an indication that a probability is above of a threshold which can be performed by a human via their mind and/or pen & paper and does not amount to significantly more.
Response to Arguments
14. Applicant's arguments filed 07/24/2026 have been fully considered but they are not persuasive.
Applicants argue on Pages 12-13 that “The Office characterizes the claims as reciting the abstract idea of "labeling data" and, more specifically, as reciting mental processes that allegedly can be performed in the human mind or with pen and paper. Applicant respectfully disagrees. The claims are not directed to a human exercise of merely assigning a label to text. Rather, the claims recite a specific computer implemented text-classification technique that uses generated positive and negative examples associated with a label description, provides those examples as input to a generative model, and determines a label probability estimate from the generative model output. As amended, claim 1 further requires that the positive example is determined based on context-aware keywords generated based on a first set of priority keywords determined based on the candidate text and a second set of priority keywords determined based on the label description. These operations are rooted in machine processing of natural-language data and generative-model outputs, not in a practically performable mental process”. However, as explained above, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example, the providing of an input of a candidate text, positive example, and negative example into a model, the determining of a label probability estimate, and the outputting of an indication on whether a candidate text corresponds to a label description based on a determined label probability estimate can all be performed by a human via their mind and/or pen & paper. Additionally, the additional element of receiving of candidate text is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Furthermore, the additional element of receiving a label description is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Moreover, the additional element of an output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application. There is no technological improvement reflected in these additional elements.
Applicants argue on Page 13 that “The specification recites that "conventional systems depend on user-provided keywords, predefined taxonomies, or large amounts of manually labeled training data, which can require substantial trial-and-error and computer processing. See, e. g. , paragraphs [0002]-[0004] and [0031]-[0034]. The claims address this technological problem in computerized text labeling and search. In particular, the disclosed system instead determines whether candidate text corresponds to a natural-language label description without requiring prior training data for that requested class, produces semantically rich positive and negative examples, and uses a generative model and label-scoring techniques to estimate whether the label applies. See, e. g. , paragraphs [0006]-[0008], [0029]-[0034], and [0092]-[0109]. These recited computer operations are not merely a result-oriented instruction to "label data," but a particular machine-implemented approach for improving automatic text classification”. However, as explained above, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example, the providing of an input of a candidate text, positive example, and negative example into a model, the determining of a label probability estimate, and the outputting of an indication on whether a candidate text corresponds to a label description based on a determined label probability estimate can all be performed by a human via their mind and/or pen & paper. Additionally, the additional element of receiving of candidate text is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Furthermore, the additional element of receiving a label description is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Moreover, the additional element of an output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application. There is no technological improvement reflected in these additional elements.
Applicants argue on Pages 13-14 that “the claims do not recite a mere mental process under MPEP § 2106. 04(a). The Office Action does not explain how a person could practically perform, in the mind or with pen and paper, the claimed generation and use of context-aware keywords, generative-model inputs and outputs, token probabilities, ranked scores, embeddings, cosine similarities, graph structures, augmented training data, and machine-learning classification recited across the claims. For at least this reason, Applicant respectfully submits that the claims do not recite a judicial exception and are patent eligible under Step 2A, Prong One. Withdrawal of the 35 U.S. C. § 101 rejection of claims 1-20 is respectfully requested”. However, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example can be performed by a human via their mind and/or pen & paper. Simply put, generating context-aware keywords is a pure mental process that a human can perform via their mind and/or pen & paper. Furthermore, the providing of an input of a candidate text, positive example, and negative example into a model can be performed by a human via their mind and/or pen & paper. Moreover, the additional element of an output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application. Additionally, a token probability is a mere mathematical operation that can be performed by a human via their mind and/or pen & paper. Furthermore, ranked scores can be generated by a human via their mind and/or pen & paper. Moreover, the generation of embeddings (and subsequent comparison) is a mere mathematical vectorization operation that can be performed by a human via their mind and/or pen & paper. Additionally, the calculation of a cosine-similarity is a mere mathematical vectorization operation that can be performed by a human via their mind and/or pen & paper. Furthermore, the storage of keywords in a graph structure is a data storage operation that is an insignificant data storage operation that does not integrate the abstract idea into a practical application. Moreover, the generation of augmented training data can be performed by a human via their mind and/or pen & paper. Additionally, the classification of data can be performed by a human via their mind and/or pen & paper.
Applicants argue on Page 14 that “Even assuming, arguendo, that the claims recite an abstract idea, the claims integrate any alleged abstract idea into a practical application. The claims do not merely collect text and report a label. Instead, the claims use a particular computer-implemented pipeline to improve automatic text labeling: receiving candidate text and a label description, obtaining positive and negative examples associated with the label description, using context-aware keywords generated from priority keywords of the candidate text and label description, providing the resulting examples to a generative model, and determining a label probability estimate based on the generative model output. These limitations meaningfully constrain how the classification is performed and tie the alleged exception to a specific technological implementation”. However, as explained above, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example, the providing of an input of a candidate text, positive example, and negative example into a model, the determining of a label probability estimate, and the outputting of an indication on whether a candidate text corresponds to a label description based on a determined label probability estimate can all be performed by a human via their mind and/or pen & paper. Additionally, the additional element of receiving of candidate text is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Furthermore, the additional element of receiving a label description is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Moreover, the additional element of an output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application. There is no technological improvement reflected in these additional elements.
Applicants argue on Page 15 that “The specification explains that this architecture improves the functioning of computerized text-classification systems by reducing the need for large manually labeled training sets and by producing semantically rich examples and context-aware keywords that reduce the amount of search processing required to return relevant results. See, e. g. , paragraphs [0007]- [0010], [0031]-[0034], [0072]-[0080], and [0120]-[0128]. The specification further describes concrete computer components and services used to implement the solution, including a labeling service, label scoring service, prioritized keyword extraction service, context-aware keyword extraction service, search service, term similarity service, vectorization functions, embedding generation models, and NLG model repository. See, e. g. , paragraphs [0055]-[0058]. These are not generic computer components invoked merely as a field of use; rather, they cooperate to generate context-aware keywords, retrieve semantically relevant examples, filter noisy candidates, and compute a label probability estimate for automatic labeling”. However, the purported technological improvements are not reflected in the claims. Specifically, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example, the providing of an input of a candidate text, positive example, and negative example into a model, the determining of a label probability estimate, and the outputting of an indication on whether a candidate text corresponds to a label description based on a determined label probability estimate can all be performed by a human via their mind and/or pen & paper. The additional elements of receiving of candidate text and receiving a label description are data gathering operations that are insignificant data gathering operations that do not integrate the abstract idea into a practical application. Moreover, the additional element of an output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application. There is no technological improvement reflected in these additional elements.
Applicants argue on Page 15 that “The present claims are therefore analogous to claims found eligible where the claimed invention improves computer-related technology by using a specific set of rules or processing steps to achieve a technological result. Here, the claimed rules and processing steps are not conventional manual labeling steps automated on a computer; they include generating or obtaining semantically rich positive and negative examples, generating context-aware keywords from priority keywords of the candidate text and label description, using generative-model outputs, and determining label probability estimates from those outputs. This ordered combination improves automatic text classification in a way that a human cannot practically perform mentally and that meaningfully limits the claim to a specific technological implementation”. However, the obtaining of a defined positive example determined based on generated context-aware keywords based on a first set of priority keywords determined based on candidate text and a second set of priority keywords determined based on a label description and a negative example, the providing of an input of a candidate text, positive example, and negative example into a model, the determining of a label probability estimate, and the outputting of an indication on whether a candidate text corresponds to a label description based on a determined label probability estimate can all be performed by a human via their mind and/or pen & paper.
Applicants argue on Pages 15-16 that “This conclusion is consistent with MPEP § 2106. 04(d)(1), which recognizes that an additional element may integrate an alleged exception into a practical application when it reflects an improvement in the functioning of a computer or another technology or technical field. Here, the amended claims improve automatic text-labeling technology by using priority keyword sets, context-aware keywords, generated examples, and generative-model scoring to reduce reliance on manually labeled training data and improve semantic retrieval and classification. Thus, even if the claims were viewed as involving labeling concepts at some level, the claims apply those concepts through a specific technological process that improves computerized text-classification functionality”. However, the additional element of receiving of candidate text is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Furthermore, the additional element of receiving a label description is a data gathering operation that is an insignificant data gathering operation that does not integrate the abstract idea into a practical application. Moreover, the additional element of an output from a model is a data output operation that is an insignificant data output operation that does not integrate the abstract idea into a practical application. There is no technological improvement reflected in these additional elements.
Conclusion
15. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. PGPUB 2022/0019730 issued to Sharma et al. on 20 January 2022. The subject matter disclosed therein is pertinent to that of claims 1-20 (e.g., methods to generate labels).
U.S. PGPUB 2021/0240781 issued to Horesh et al. on 05 August 2021. The subject matter disclosed therein is pertinent to that of claims 1-20 (e.g., methods to generate labels).
16. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contact Information
17. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Mahesh Dwivedi whose telephone number is (571) 272-2731. The examiner can normally be reached on Monday to Friday 8:20 am – 4:40 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Charles Rones can be reached (571) 272-4085. The fax number for the organization where this application or proceeding is assigned is (571) 273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free).
Mahesh Dwivedi
Primary Examiner
Art Unit 2168
September 07, 2026
/MAHESH H DWIVEDI/Primary Examiner, Art Unit 2168
Prosecution Insights